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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationTue, 18 Oct 2011 08:23:13 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/18/t131894061209wzxza794lovwi.htm/, Retrieved Fri, 03 May 2024 21:31:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=131748, Retrieved Fri, 03 May 2024 21:31:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact297

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- R PD  [Survey Scores] [] [2011-10-18 12:18:26] [b98453cac15ba1066b407e146608df68]
-    D    [Survey Scores] [] [2011-10-18 12:21:42] [b98453cac15ba1066b407e146608df68]
-    D        [Survey Scores] [] [2011-10-18 12:23:13] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- R             [Survey Scores] [] [2011-10-25 13:47:38] [19d77e37efa419fdc040c74a96874aff]
- R             [Survey Scores] [] [2011-12-01 13:03:23] [aefb5c2d4042694c5b6b82f93ac1885a]
- R             [Survey Scores] [E3] [2012-11-06 20:34:44] [ec67509cb0a58a77552cc42e4bdf733e]
- R             [Survey Scores] [paper one sample ...] [2012-12-05 16:34:46] [1edfe4f7de973a74350ac08c1294a22c]
- R             [Survey Scores] [] [2012-12-17 18:39:53] [edf0418499cd31d27dbea8ea1d30b3db]
-                 [Survey Scores] [deel 1 pearsonE3] [2012-12-20 19:29:30] [74be16979710d4c4e7c6647856088456]
- RM            [Survey Scores] [] [2014-10-15 08:07:04] [eee95947b6243a1febfcd5f41483d733]
- RM            [Survey Scores] [] [2014-10-15 10:37:08] [394a9522c47495260fca596e959e6202]
- RM            [Survey Scores] [E3] [2014-10-15 11:00:28] [508ad00fbaced7ad8e80ddb3167ea0fd]
- RM            [Survey Scores] [E3] [2014-10-15 11:11:10] [56d77bf8347cfd1e104fa9098ce46dbd]
- RM            [Survey Scores] [] [2014-10-15 11:45:49] [95c11abf048d3a1e472aeccb09199113]
- RM            [Survey Scores] [] [2014-10-15 11:51:39] [fa1b8827d7de91b8b87087311d3d9fa1]
- RM            [Survey Scores] [WS3 Question 1] [2014-10-15 12:09:34] [f13ab2b9cdb9c17a0cf473fdf5cac3ab]
- RM            [Survey Scores] [WS3 task1cc] [2014-10-15 12:15:45] [46c7ebd23dbdec306a09830d8b7528e7]
- RM            [Survey Scores] [WS3-task1E3] [2014-10-15 12:16:31] [81f624c2f0b20a2549c93e7c3dccf981]
- RM            [Survey Scores] [ws3] [2014-10-15 12:40:15] [bcd8153d44f369b7624d3c1b4621c4c3]
- RM            [Survey Scores] [] [2014-10-15 12:48:05] [eee95947b6243a1febfcd5f41483d733]
- RM            [Survey Scores] [Q1] [2014-10-15 12:49:45] [bcf5edf18529a33bd1494456d2c6cb9a]
- RM            [Survey Scores] [] [2014-10-15 12:52:24] [eee95947b6243a1febfcd5f41483d733]
- RM            [Survey Scores] [Kendall tau] [2014-10-15 12:55:25] [ae96d02647dd9ad9c105f1fa6642e295]
- RM            [Survey Scores] [E3 kendall] [2014-10-15 13:02:38] [e3727f74ca0896859afbe865e40a3465]
- RM            [Survey Scores] [] [2014-10-15 13:03:11] [6795cd14e59cd8fafcdf800c40b889d9]
- RM            [Survey Scores] [] [2014-10-15 13:13:00] [63554e339c9381d8e23ab848f4176daf]
- RM            [Survey Scores] [Task 1.3 WS3] [2014-10-15 13:15:53] [805021881bfa5340347077d26b077617]
- RMP           [Survey Scores] [] [2014-10-15 13:16:31] [bcf5edf18529a33bd1494456d2c6cb9a]
- RM            [Survey Scores] [E3] [2014-10-15 13:22:31] [2ba32e9656c7c3fdddad3ba3f1588288]
- RM            [Survey Scores] [] [2014-10-15 13:25:14] [fda96889f4ef6d31c0c28fd64d281011]
- RMP           [Survey Scores] [] [2014-10-15 14:00:23] [bcf5edf18529a33bd1494456d2c6cb9a]
- RM            [Survey Scores] [WS3 Question1.2] [2014-10-15 14:17:41] [ce9f16fa58bb2303d66047ab4343b505]
- RM            [Survey Scores] [] [2014-10-15 14:30:10] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM            [Survey Scores] [WS3 SHW] [2014-10-15 14:30:34] [cac6c5fb035463be46c296b46e439cb5]
- RM            [Survey Scores] [] [2014-10-15 14:38:14] [8d160a85bfd9526a7d0e42afc5fb569b]
- RM            [Survey Scores] [] [2014-10-15 15:18:07] [dacad244957cb51472792888970d4390]
- RM            [Survey Scores] [WSH 3, Task 1b] [2014-10-15 15:25:05] [e7da31d1eb6eab8d5ed70d87d07c747b]
- RM            [Survey Scores] [] [2014-10-15 16:40:47] [bca3c6529212edfac3e771806c79a908]
- RM            [Survey Scores] [] [2014-10-15 17:00:14] [261f60062b6e70d0e3f72a6ad4f04654]
- RM            [Survey Scores] [] [2014-10-15 17:11:53] [69bf0eb8b9b38defaaf4848d8c317571]
- RM            [Survey Scores] [WS3Q1] [2014-10-15 17:29:43] [1a6d42b46b3d01bc960fcfb45e99fecd]
- RM            [Survey Scores] [ws3 task 2,3] [2014-10-15 17:57:55] [99723d3e379f668157309b7b2091b15d]
- RM            [Survey Scores] [WS3 Q1] [2014-10-15 18:06:00] [8523551e1e4e3cbe97fa25692e177b2e]
- RM            [Survey Scores] [] [2014-10-16 08:33:58] [044144d0728beecdb08e0d94daaff202]
- RM            [Survey Scores] [] [2014-10-16 13:40:48] [4c4ebb0b36a379d1d949ba77427e658a]
- RM            [Survey Scores] [task 2 e3] [2014-10-16 15:15:22] [673773038936aef3a5778d7e6bda5c1e]
- RM            [Survey Scores] [] [2014-10-16 15:21:46] [765bd0d5d4a0c852014c120c6930661d]
- RM            [Survey Scores] [ws3 6] [2014-10-16 15:23:06] [ce58fb8a0a6d5fe2eedf5e527a9cf2f2]
- RM            [Survey Scores] [qsfd] [2014-10-16 15:23:35] [118a39334d200089014f927b57d44a19]
- RM            [Survey Scores] [Kendall tau E3] [2014-10-16 16:21:23] [55a850ac261e4a7d4f206113c00d6f60]
- RM            [Survey Scores] [] [2014-10-16 16:27:07] [784816b0c716a476fc48ddde921cf7ea]

[Truncated]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	7	5	7
5	5	5	5
4	6	5	5
3	6	6	6
6	6	6	6
5	5	5	7
5	7	5	6
1	6	6	7
4	7	7	7
5	6	6	6
6	7	7	7
7	7	6	7
5	6	6	5
6	6	6	6
5	7	6	7
4	6	6	6
7	7	7	7
7	7	7	7
6	7	7	7
6	7	6	6
2	5	5	4
7	7	7	7
5	5	5	6
4	6	7	7
7	7	6	7
1	6	2	5
1	6	2	5
7	6	7	7
4	6	4	6
5	6	4	6
5	6	5	6
5	5	5	6
4	3	4	1
5	3	7	5
5	5	7	7
4	6	4	5
7	7	7	7
7	7	4	5
7	7	6	7
4	6	6	6
7	7	6	7
7	7	6	6
4	6	6	6
3	6	7	5
2	5	6	6
6	6	6	6
4	6	4	5
5	7	7	7
4	6	6	6
7	7	7	7
4	6	6	5
6	5	7	5
7	7	7	7
1	4	2	3
5	7	6	6
4	5	6	6
5	6	5	5
5	7	6	6
5	7	6	6
5	7	6	7
5	7	6	7
5	6	6	6
6	6	4	5
3	6	3	4
4	4	4	5
6	6	7	6
6	6	6	6
3	7	6	7
5	7	7	6
2	7	7	7
7	7	7	7
7	7	5	7
4	6	6	6
6	5	3	5
6	7	6	7
3	5	5	5
3	5	5	5
6	7	6	6
7	7	6	7
3	2	4	3
1	6	4	4
5	6	5	5
5	6	6	6
5	6	5	6
5	5	5	6
6	6	6	6
6	7	7	7
5	5	5	7
7	7	7	7
6	6	7	7
1	5	2	2
3	6	5	5
5	7	4	6
1	7	7	6
6	6	6	6
4	7	7	7
5	6	5	5
5	5	5	5
6	5	4	6
5	6	7	6
5	6	5	7
4	6	4	4
6	6	6	6
6	6	6	6
4	5	5	5
5	5	5	5
5	5	3	5
2	7	5	6
7	7	6	7
5	6	6	6
5	7	7	7
2	7	7	7
3	4	5	5
5	5	5	6
5	7	6	7
5	7	4	7
6	7	7	7
6	6	5	7
4	5	6	5
6	7	7	7
3	4	7	7
6	6	6	6
4	6	6	5
3	3	4	5
4	7	7	7
6	6	6	7
4	7	5	6
6	6	6	6
5	5	5	6
5	6	5	6
5	6	6	6
3	7	6	6
5	6	4	5
4	7	6	6
5	6	7	7
5	6	6	6
1	7	7	7
4	7	7	7
7	7	6	6
4	7	5	6
6	6	5	7
7	7	5	5
6	7	7	5
5	6	3	6
6	7	6	7
5	6	5	5
5	7	7	7
6	6	4	5
5	5	6	6
3	4	4	5
6	7	6	7
7	7	7	7
4	5	4	5
5	7	6	7
4	6	7	6
5	5	5	6
2	6	6	6
7	7	4	7
5	7	4	6
4	6	6	5
2	5	4	5
4	6	3	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131748&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131748&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131748&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net






Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.79179510.56104280.58
22.0834250.9715340.95
31.56266130.9113190.87
41.9632570.9615440.95

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 0.79 & 179 & 51 & 0.56 & 104 & 28 & 0.58 \tabularnewline
2 & 2.08 & 342 & 5 & 0.97 & 153 & 4 & 0.95 \tabularnewline
3 & 1.56 & 266 & 13 & 0.91 & 131 & 9 & 0.87 \tabularnewline
4 & 1.96 & 325 & 7 & 0.96 & 154 & 4 & 0.95 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131748&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]0.79[/C][C]179[/C][C]51[/C][C]0.56[/C][C]104[/C][C]28[/C][C]0.58[/C][/ROW]
[ROW][C]2[/C][C]2.08[/C][C]342[/C][C]5[/C][C]0.97[/C][C]153[/C][C]4[/C][C]0.95[/C][/ROW]
[ROW][C]3[/C][C]1.56[/C][C]266[/C][C]13[/C][C]0.91[/C][C]131[/C][C]9[/C][C]0.87[/C][/ROW]
[ROW][C]4[/C][C]1.96[/C][C]325[/C][C]7[/C][C]0.96[/C][C]154[/C][C]4[/C][C]0.95[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131748&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131748&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
10.79179510.56104280.58
22.0834250.9715340.95
31.56266130.9113190.87
41.9632570.9615440.95






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.967 (0.033)0.983 (0.017)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.996 (0.004)
(Pc-Nc)/(Pc+Nc)0.983 (0.017)0.996 (0.004)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.967 (0.033) & 0.983 (0.017) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.967 (0.033) & 1 (0) & 0.996 (0.004) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.983 (0.017) & 0.996 (0.004) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131748&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.967 (0.033)[/C][C]0.983 (0.017)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.967 (0.033)[/C][C]1 (0)[/C][C]0.996 (0.004)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.983 (0.017)[/C][C]0.996 (0.004)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131748&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131748&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.967 (0.033)0.983 (0.017)
(Ps-Ns)/(Ps+Ns)0.967 (0.033)1 (0)0.996 (0.004)
(Pc-Nc)/(Pc+Nc)0.983 (0.017)0.996 (0.004)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)0.913 (0.071)1 (0.056)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0.083) & 1 (0.083) & 0.913 (0.071) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 0.913 (0.071) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.913 (0.071) & 0.913 (0.071) & 1 (0.056) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131748&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]0.913 (0.071)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]0.913 (0.071)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.913 (0.071)[/C][C]0.913 (0.071)[/C][C]1 (0.056)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131748&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131748&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)0.913 (0.071)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)0.913 (0.071)
(Pc-Nc)/(Pc+Nc)0.913 (0.071)0.913 (0.071)1 (0.056)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 1 2 3 4 5 6 7 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')